Senior Associate/Assistant Vice President, AI Data Engineer
Temasek Holdings (Private) Limited3 months ago
Singapore, SingaporeMid Level / Senior
Responsibilities
- Design and build AI-ready data architectures using structured data stores, vector knowledge bases, graph databases, and hybrid retrieval systems.
- Build and maintain RAG data layers, including document ingestion, chunking, embedding generation, metadata tagging, and vector index management.
- Define ontology and schema standards for AI-accessible data assets.
- Architect real-time and near-real-time market, research, news, and portfolio data feeds with enforced freshness and latency SLAs.
- Implement data quality standards, automated quality gates, lineage tracking, observability, drift detection, schema alerts, and SLA dashboards.
- Ensure AI data assets meet data classification, access control, governance, audit, and cross-border data handling requirements.
- Build reusable investment knowledge graphs, data APIs, document intelligence pipelines, and portfolio analytics data services.
- Maintain the AI data catalogue and contribute to enterprise data platform strategy.
- Evaluate and manage external data vendors, market data providers, data quality assessments, and licensing agreements.
Requirements
- 4–8 years of data engineering experience, including at least 2 years building production data infrastructure for AI/ML or LLM-powered systems.
- Experience working in data-intensive organizations with complex heterogeneous environments; investment, financial, or enterprise data experience is preferred.
- Production experience building RAG pipelines or AI knowledge bases, including vector store management, embedding pipelines, and chunking strategy optimization.
- Strong fundamentals in pipeline design and orchestration, schema design, data quality frameworks, and lineage tracking.
- Proficiency with Python, pandas, Polars, SQLAlchemy, dbt, Apache Airflow or Prefect, and Spark.
- Experience with batch and streaming architectures using Kafka, Kinesis, or equivalent technologies.
- Experience with vector databases such as Pinecone, Weaviate, pgvector, and Chroma, plus embedding model management.
- Experience with LlamaIndex or LangChain data connectors, document parsing, OCR tooling, and document chunking strategies.
- SQL proficiency across multiple dialects and experience with Snowflake, BigQuery, Redshift, or Databricks.
- Familiarity with graph database concepts and Neo4j or equivalent.
- Experience with data quality tools such as Great Expectations or Soda, lineage tools such as OpenLineage, DataHub, or Marquez, and observability platforms such as Monte Carlo or Acceldata.
- Exposure to investment data domains, including company financials, market data, and portfolio systems, is preferred.
Tech Stack
Amazon RedshiftApache AirflowApache KafkaApache SparkDatabricksdbtGoogle BigQueryNeo4jPandasPythonSnowflakeSQL
Categories
Data Engineering
About Temasek Holdings (Private) Limited
Temasek Holdings is a Singapore-headquartered global investment company that deploys capital across public and private markets, from venture to large-cap equities, to generate long-term, sustainable returns. Wholly owned by the Singapore government and founded in 1974, it manages a portfolio of roughly S$500 billion and operates offices across Asia, the Americas, and Europe. It invests directly in companies and funds, and stewards holdings across sectors such as technology, life sciences, financial services, and energy.